Instructions to use hf-internal-testing/tiny-random-Blip2ForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Blip2ForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("visual-question-answering", model="hf-internal-testing/tiny-random-Blip2ForConditionalGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-Blip2ForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-Blip2ForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 899 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-Blip2ForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Blip2ForConditionalGeneration@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-Blip2ForConditionalGeneration/resolve/refs%2Fpr%2F1/model.safetensors
899 kB
- Xet hash:
- ec15c6095be59c9b3ad64705865f920d3b180c1fcaa5d80de582e433b459122e
- Size of remote file:
- 899 kB
- SHA256:
- e84aa733ff9bae4936c6190d73fc6bd236749f57db51428a7208a4bd30d6a9a5
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